Open projects and theses

On this webpage we present topics that can lead to BSc/MSc projects or theses in Computer Science or Cognitive Science. As our research focus is highly interdisciplinary we can offer a bandwith of projects that may have an empirical/experimental or more theoretic approach. In any case please contact Marco Ragni directly, if you are interested.

Topic 1: Probabilities and Ranks in Human Non-Monotonic Reasoning

Target group: MSc (Computer Science)

Bayes-in-the-head theories of cognition assume that humans calculate or approximate Bayesian statistics for everyday reasoning. Other approaches, however, assume mental representations with a qualitative ordering on models. From a formal perspective, it is an open question which of these approaches predicts human reasoning behavior the best. The goal is to compare, implement and evaluate the theories against empirical data.

Requirements:

Programming in Python

Interest in formal logics

Topic 2: Predictive models for individual human reasoning

For given information what inferences do humans draw in general? Going one step further: Is it possible to predict for some background knowledge like working memory size and inferences drawn for some problem instances what the subject draws for an inference for a similar problem? What about a not so similar problem?

Requirements:

Knowledge of Python

Interest in probabilistic modeling

Topic 3: Genetic programming for automatic generation of heuristics

Target group: BSc/MSc (Computer Science / Cognitive Science)

Decisions human make can depend on heuristics. In this thesis you will start with analyzing existing heuristics and then try to automatically generate heuristics that can fit better human decisions than existing ones.

Requirements:

Knowledge of Python

Some knowledge about AI foundations

Topic 4: Formalization and Evaluation of Cognitive Theories

Target group: MSc/BSc (Computer Science / Cognitive Science)

How can we compare different cognitive theories? Mathematical psychology offers interesting approaches to evaluate theories using AIC, BIC, DIC etc. Multinomial process trees offer an excellent possibility to formalize cognitive theories (especially for research on recognition memory. Their expressiveness, however, and their application on human reasoning still requires more research.

Requirements:

Knowledge of R

Mathematical knowledge (statistics)

Topic 5: Modelling Reasoning in the Neural Engineering Framework

Target group: BSc/MSc (Computer Science/Cognitive Science)

This project is about the modelling of reasoning processes in the Neural Engineering Framework (NEF). The NEF is a cognitive architecture framework which is based on physiologically plausible neural clusters. The goal is to implement a model which is able to solve reasoning and tasks and afterwards to evaluate the results and the model. In the end, we would like to find out how algorithms have to be implemented in neurons in order to exhibit human-like behavior.

Requirements:

Programming in Python

Some knowledge about cognitive neuroscience and/or interest in learning about it

Topic 6: Modeling common sense reasoning

Target group: MSc (Computer Science / Cognitive Science)

Problems such as the Winnograd challenge or PDP-Problems are considered very hard AI problems. Such problems are typically very easy to solve for human reasoners but are very difficult for current Machine Learning approaches as they require some form of semantic understanding.